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Handelsregister

by io.github.jkbngb

Dataset coverage per country

get_coverage
Read-onlyIdempotent

Dataset coverage and the capability matrix, per country. Read-only. CALL THIS FIRST before concluding that something does not exist in a country.

    Parameters:
    - country (optional, default "all"): "AT" | "DE" | "all" - which countries to include.

    Returns {countries: {<code>: <that backend's coverage payload>}, capabilities,
    countries_unavailable}. Each country section is the country backend's own coverage
    dashboard (AT: parsed-financials counts by format/status; DE: per-Bundesland counts
    + fill rates - the DE backfill is still running, so a low count means "not crawled
    yet", not "does not exist"). ``capabilities`` is the machine-readable matrix of what
    each country supports (financials, documents, events windows, filters); a country
    that cannot be reached appears under ``countries_unavailable`` with the error
    instead of failing the whole call. For valid filter values use describe_fields;
    for per-company data use search_companies.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countryNoall

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint and idempotentHint, but the description adds valuable behavioral context: it explains countries_unavailable behavior, the backfill caveat for DE counts, and how not to interpret low counts. This clearly exceeds the annotation baseline and helps the agent avoid incorrect conclusions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but well-structured: a one-line usage cue, a compact parameter section, and a return-shape explanation. Every sentence adds necessary information, and the critical 'call first' guidance is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the single optional parameter, the return structure, error handling for unreachable countries, and the meaning of incomplete data. Given the output schema and sibling context already provided, nothing necessary for safe and correct invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description is the only source of parameter meaning. It explains the country parameter is optional, defaults to "all", and defines the allowed values "AT", "DE", and "all". It also clarifies how the parameter affects the returned payload.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns dataset coverage and a capability matrix per country, which is a specific resource and purpose rather than a tautology. It also distinguishes itself from sibling tools by explicitly routing to describe_fields for filter values and search_companies for per-company data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives an explicit directive: 'CALL THIS FIRST before concluding that something does not exist in a country.' It also names alternatives and the conditions under which they should be used, making the selection decision clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Handelsregister toolsInspect
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TDQS

A4.8/5.0
Disambiguation4/5

Each tool has a distinct primary purpose, with clear pointers to the right tool for the job. The main possible confusion is between describe_fields/get_coverage and search_companies/search_person, but the descriptions actively disambiguate those boundaries.

Naming Consistency5/5

All tool names follow a consistent lowercase snake_case verb_noun pattern: describe_fields, export_companies_csv, get_company_details, list_events, search_companies. Even ping fits the predictable style as a simple liveness verb.

Tool Count5/5

Eleven tools is well-scoped for a unified company-register facade. Each tool covers a distinct part of the surface: schema, coverage, search, detail, persons, peers, events, statistics, export, and diagnostics.

Completeness5/5

The read-only domain is covered thoroughly: lookup, detail, person search, similarity, event feeds, aggregate stats, and export all exist. Unsupported country-specific features are handled with notices and coverage metadata rather than missing tooling.

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